title: Tubule detection in testis images using boundary weighting and circular shortest path.
abstract: In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually.
authors.forename: Chao
authors.initials: C
authors.lastname: Zhang
authors.forename: Changming
authors.initials: C
authors.lastname: Sun
authors.forename: Rhonda
authors.initials: R
authors.lastname: Davey
authors.forename: Ran
authors.initials: R
authors.lastname: Su
authors.forename: Leanne
authors.initials: L
authors.lastname: Bischof
authors.forename: Pascal
authors.initials: P
authors.lastname: Vallotton
authors.forename: David
authors.initials: D
authors.lastname: Lovell
authors.forename: Shelly
authors.initials: S
authors.lastname: Hope
authors.forename: Sigrid
authors.initials: S
authors.lastname: Lehnert
authors.forename: Tuan D
authors.initials: TD
authors.lastname: Pham
mesh_terms: D000465:Algorithms; D002452:Cell Count; D005854:Germ Cells / Q000166:cytology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D012671:Seminiferous Tubules / Q000033:anatomy & histology*